US11434522B1 - Detection of chromosome interactions - Google Patents

Detection of chromosome interactions Download PDF

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US11434522B1
US11434522B1 US15/738,476 US201615738476A US11434522B1 US 11434522 B1 US11434522 B1 US 11434522B1 US 201615738476 A US201615738476 A US 201615738476A US 11434522 B1 US11434522 B1 US 11434522B1
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chromosome
mtx
interactions
nucleic acids
disease
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Ewan Hunter
Aroul Ramadass
Alexandre Akoulitchev
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Oxford Biodynamics PLC
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Definitions

  • the invention relates to detecting chromosome interactions.
  • Health care costs are spiralling and so there is a need to treat people more effectively using existing drugs.
  • the inventors have investigated the use of epigenetic chromosome interactions as the basis of or for use in conjunction with companion diagnostics, and in particular in the detection of epigenetic states to determine responsiveness to therapy (e.g. pharmaceutical therapy), predisposition to disease/conditions, and/or monitoring residual disease.
  • the inventors' work shows the role played by epigenetic interactions in a diverse set of conditions and provides methods for identifying the relevant chromosomal interactions.
  • the invention includes a method of identifying relevant chromosomal interactions based on looking at the chromosome interactions present in subgroups of individuals.
  • the invention also includes using the identified chromosome interactions as the basis for companion diagnostic tests.
  • a first aspect of the invention provides a method of determining the epigenetic chromosome interactions which are relevant to a companion diagnostic that distinguishes between subgroups, comprising contacting a first set of nucleic acids from the subgroups with a second set of nucleic acids representing an index population of chromosome interactions, and allowing complementary sequences to hybridise, wherein the nucleic acids in the first and second sets of nucleic acids represent a ligated product comprising sequences from both of the chromosome regions that have come together in the epigenetic chromosome interaction, and wherein the pattern of hybridisation between the first and second set of nucleic acids allows a determination of which epigenetic chromosome interactions are specific to subgroups in the population, wherein the subgroups differ in a characteristic relevant to a companion diagnostic.
  • the feature “ . . . the nucleic acids in the first and second sets of nucleic acids represent a ligated product comprising sequences from both of the chromosome regions that have come together in the epigenetic chromosome interaction . . . ” can comprise or be: “ . . . the nucleic acids in the first and second sets of nucleic acids are in the form of a ligated product(s) (preferably a ligated nucleic acid(s), more preferably ligated DNA) comprising sequences from both of the chromosome regions that have come together in the epigenetic chromosome interaction”.
  • a ligated product(s) preferably a ligated nucleic acid(s), more preferably ligated DNA
  • a second aspect of the invention provides a companion diagnostic assay method which selects a subgroup having a characteristic relevant to treatment and/or prophylaxis (in particular pharmaceutical treatment and/or prophylaxis), which method comprises:
  • the companion diagnostic assay method of the second aspect of the invention can particularly be used to detect the presence of any of the specific conditions or characteristics mentioned herein.
  • the companion diagnostic method of the second aspect of the invention is used to detect:
  • the disease or condition (in particular in a human) comprises:
  • responsiveness to therapy is detected in any of the following cancers, preferably of the stage or class which is indicated and/or preferably with other indicated characteristics such as viral infection:
  • a third aspect of the present invention provides a therapeutic agent (in particular a pharmaceutical therapeutic agent) for use in the treatment and/or prophylaxis of a condition in an individual (in particular in a human individual), wherein said individual has been identified as being in need of said therapeutic agent by the method of the second aspect of the invention.
  • the third aspect of the invention also provides the use of a therapeutic agent (e.g. pharmaceutical therapeutic agent) in the manufacture of a medicament (in particular a pharmaceutical composition comprising the therapeutic agent) for use in the treatment and/or prophylaxis of a condition in an individual (in particular in a human individual), wherein said individual has been identified as being in need of said therapeutic agent by the method of the second aspect of the invention.
  • the third aspect of the present invention also provides a method of treatment and/or prophylaxis of a condition in an individual (in particular in a human individual and/or an individual in need thereof), comprising administering a therapeutic agent (e.g. pharmaceutical therapeutic agent and/or an effective amount of a therapeutic agent) to the individual, wherein said individual has been identified as being in need of said therapeutic agent by the method of the second aspect of the invention.
  • a therapeutic agent e.g. pharmaceutical therapeutic agent and/or an effective amount of a therapeutic agent
  • the therapeutic agent in particular pharmaceutical therapeutic agent, comprises:
  • a fourth aspect of the invention provides a method of identifying an agent which is capable of changing the disease state of an individual from a first state to a second state comprising determining whether a candidate agent is capable of changing the chromosomal interactions from those corresponding with the first state to chromosomal interactions which correspond to the second state, wherein preferably the first and second state correspond to presence or absence of:
  • a fifth aspect of the invention provides a method of determining the effect of a drug comprising detecting the change in epigenetic chromosome interactions caused by the drug, wherein said effect is preferably the mechanism of action of the drug or are the pharmacodynamics properties of the drug, and wherein said the chromosome interactions are preferably specific to:
  • the present invention does not relate to a method of determining responsiveness to a specific therapy (in particular a specific pharmaceutical therapy) for rheumatoid arthritis in a subject (e.g. a mammalian such as human subject), comprising detecting the presence or absence of 5 or more (in particular 7 or more, or 10 or more, or 15 or more, or 20 or more) chromosomal interactions; wherein said chromosomal interactions are in particular at 5 or more (for example 5) different loci; and/or wherein said detecting in particular comprises determining for each interaction whether or not the regions of a chromosome which are part of the interaction have been brought together.
  • a specific therapy in particular a specific pharmaceutical therapy
  • a subject e.g. a mammalian such as human subject
  • FIG. 1 is a figure comprising pie-charts and graphs relating to: Chromosome Conformation Signature EpiSwitchTM Markers discriminate MTX responders (R) from non-responders (NR).
  • R Chromosome Conformation Signature EpiSwitchTM Markers discriminate MTX responders (R) from non-responders (NR).
  • a discovery cohort of responder (R) and non-responder (NR) RA patients were selected based on DAS28 (Disease Activity Score of 28 joints) EULAR (The European League against Rheumatism) response criteria (see methods).
  • DAS28 Disease Activity Score of 28 joints
  • EULAR The European League against Rheumatism
  • C EpiSwitchTM array analysis of peripheral blood mononuclear cells taken at diagnosis from R and NR, and healthy controls (HC) identified 922 statistically significant stratifying marker candidates. Further analysis revealed that 420 were specific for NR, 210 to R and 159 to HC. Pie charts show the proportion in relation to the 13,322 conditional chromosome conformations screened. All markers showed adjusted p ⁇ 0.2.
  • D Hierarchical clustering using Manhattan distance measure with complete linkage agglomeration is shown by the heatmaps. Marker selection using binary pattering across the 3 groups (R, NR and HC) initially reduced the 922 EpiSwitchTM Markers to 65 and then the top 30 markers.
  • FIG. 2 is a figure comprising pie-charts and graphs relating to: Refinement and validation of the Chromosome Conformation Signature EpiSwitchTM Markers.
  • the validation cohort of responder (R) and non-responder (NR) RA patients were selected based on DAS28 (Disease Activity Score of 28 joints) EULAR (The European League against Rheumatism) response criteria (see methods).
  • B CDAI scores of R and NR patients at baseline and 6 months. ****P ⁇ 0.0001 by Kruskal-Wallis test with Dunn's multiple comparison post-test
  • C Correlation plot of the classifying 5 EpiSwitchTM markers. The red box indicates the markers that define NR whilst the orange box indicated markers that define R.
  • PCA Principle Component Analysis
  • FIG. 3 is a figure comprising graphs relating to: Prognostic stratification and model validation for response to methotrexate (MTX) treatment.
  • A Representative examples of 5 selected Receiver Operating Characteristics (ROC) curves from 150 randomisations of the data using the 5 CCS marker logistic regression classifiers.
  • B Factor Analysis for responder (R) and non-responder (NR) RA patients vs healthy controls (HC) using EpiSwitchTM CCS markers selected for discerning MTX responders from MTX non-responders.
  • FIG. 4 is a Schematic diagram of the 3C extraction process.
  • 3C means chromatin conformation capture, or chromosome conformation capture.
  • FIG. 5 is a Scheme illustrating the Design for Discovery and Validation of Epigenetic Stratifying Biomarker Signature for DMARDS Na ⁇ ve ERA patients, who were confirmed within 6 months of MTX treatment as responders (N) or non-responders (NR).
  • Epigenetic stratification was based on conditional chromosome confirmations screened and monitored by EpiSwitchTM Array and PCR (polymerase chain reaction) platforms.
  • Disease specific epigenetic nature of the identified biomarkers was confirmed by stratification against healthy controls (HC). Validation was performed on 60 RA patients (30 responders and 30 non-responders) and 30 HC.
  • the invention has several different aspects:
  • epigenetic interactions typically refers to interactions between distal regions of a locus on a chromosome, said interactions being dynamic and altering, forming or breaking depending upon the status of the region of the chromosome.
  • chromosome interactions are detected by first generating a ligated nucleic acid that comprises sequence(s) from both regions of the chromosomes that are part of the chromosome interactions.
  • the regions can be cross-linked by any suitable means.
  • the interactions are cross-linked using formaldehyde, but may also be cross-linked by any aldehyde, or D-Biotinoyl-e-aminocaproic acid-N-hydroxysuccinimide ester or Digoxigenin-3-O-methylcarbonyl-e-aminocaproic acid-N-hydroxysuccinimide ester.
  • Para-formaldehyde can cross link DNA chains which are 4 Angstroms apart.
  • the chromosome interaction may reflect the status of the region of the chromosome, for example, if it is being transcribed or repressed in response to change of the physiological conditions. Chromosome interactions which are specific to subgroups as defined herein have been found to be stable, thus providing a reliable means of measuring the differences between the two subgroups.
  • chromosome interactions specific to a disease condition will normally occur early in the disease process, for example compared to other epigenetic markers such as methylation or changes to binding of histone proteins.
  • the companion diagnostic method of the invention is able to detect early stages of a disease state. This allows early treatment which may as a consequence be more effective.
  • Another advantage of the invention is that no prior knowledge is needed about which loci are relevant for identification of relevant chromosome interactions. Furthermore there is little variation in the relevant chromosome interactions between individuals within the same subgroup. Detecting chromosome interactions is highly informative with up to 50 different possible interactions per gene, and so methods of the invention can interrogate 500,000 different interactions.
  • Epigenetic chromosomal interactions may overlap and include the regions of chromosomes shown to encode relevant or undescribed genes, but equally may be in intergenic regions. It should further be noted that the inventors have discovered that epigenetic interactions in all regions are equally important in determining the status of the chromosomal locus. These interactions are not necessarily in the coding region of a particular gene located at the locus and may be in intergenic regions.
  • the chromosome interactions which are detected in the invention could be caused by changes to the underlying DNA sequence, by environmental factors, DNA methylation, non-coding antisense RNA transcripts, non-mutagenic carcinogens, histone modifications, chromatin remodelling and specific local DNA interactions.
  • the changes which lead to the chromosome interactions may be caused by changes to the underlying nucleic acid sequence, which themselves do not directly affect a gene product or the mode of gene expression.
  • Such changes may be for example, SNP's within and/or outside of the genes, gene fusions and/or deletions of intergenic DNA, microRNA, and non-coding RNA.
  • SNP's within and/or outside of the genes, gene fusions and/or deletions of intergenic DNA, microRNA, and non-coding RNA.
  • the regions of the chromosome which come together to form the interaction are less than 5 k
  • the chromosome interaction which is detected in the companion diagnostic method is preferably one which is within any of the genes mentioned in the Tables herein. However it may also be upstream or downstream of the genes, for example up to 50,000, 30,000, 20,000, 10,000 or 5000 bases upstream or downstream from the gene or from the coding sequence.
  • the chromosome interaction which is detected may or may not be one which occurs between a gene (including coding sequence) and its regulatory region, such as a promoter.
  • the chromosome interaction which is typed may or may not be one which is inherited, for example an inherited imprinted characteristic of a gene region.
  • RA Heumatoid Arthritis
  • MTX methotrexate
  • the aim of the present invention is to permit detection and monitoring of disease.
  • this technology allows stratification based on biomarkers for specific phenotypes relating to medical conditions, i.e. by recognising a particular chromosome confirmation signature and/or a change in that particular signature.
  • the methods of the invention are preferably used in the context of specific characteristics relating to disease, such as responsiveness to treatments and/or prophylaxes, identification of the most effective therapy/drug, monitoring the course of disease, identifying predisposition to disease, and/or identifying the presence of residual disease and/or the likelihood of relapse. Therefore the methods may or may not be used for diagnosis of the presence of a specific condition.
  • the methods of the invention can be used to type loci where the mechanisms of disease are unknown, unclear or complex.
  • Detection of chromosome interactions provides an efficient way of following changes at the different levels of regulation, some of which are complex. For example in some cases around 37,000 non-coding RNAs can be activated by a single impulse.
  • a “subgroup” preferably refers to a population subgroup (a subgroup in a population), more preferably a subgroup in a or the population of a particular animal such as a particular mammal (e.g. human, non-human primate, or rodent e.g. mouse or rat) or a particular nematode worm (e.g. C. elegans ). Most preferably, a “subgroup” refers to a subgroup in a or the human population.
  • a particular mammal e.g. human, non-human primate, or rodent e.g. mouse or rat
  • a particular nematode worm e.g. C. elegans
  • Particular populations, e.g. human populations, of interest include: the human population overall, a or the human population suffering from a specific condition/disease (in particular inflammatory disease e.g. RA, blood cancer eg AML, solid cancer eg melanoma or prostate cancer (PC), or neurodegenerative disease/condition e.g. Alzheimer's disease (AD)), the human healthy population (healthy controls), the human population which is healthy in the sense of not suffering from the specific condition/disease of interest or of study (eg RA, AML, melanoma, PC or AD), the human population (e.g. either healthy and/or with a specific condition/disease e.g.
  • a specific condition/disease in particular inflammatory disease e.g. RA, blood cancer eg AML, solid cancer eg melanoma or prostate cancer (PC), or neurodegenerative disease/condition e.g. Alzheimer's disease (AD)
  • the human healthy population health controls
  • RA RA, AML, melanoma, PC or AD
  • responders to a particular drug/therapy or the human population (e.g. either healthy and/or with a specific condition/disease e.g. RA, AML, melanoma, PC or AD) who are non-responders to a particular drug/therapy.
  • human population e.g. either healthy and/or with a specific condition/disease e.g. RA, AML, melanoma, PC or AD
  • non-responders to a particular drug/therapy e.g. either healthy and/or with a specific condition/disease e.g. RA, AML, melanoma, PC or AD
  • the invention relates to detecting and treating particular subgroups in a population, preferably in a or the human population.
  • the characteristics discussed herein such as responsiveness to treatment and/or prophylaxis; in particular responsiveness to a specific treatment and/or prophylaxis of one or more conditions or diseases, and/or responsiveness to a specific medicine or therapeutically active substance/therapeutic agent, in particular in the treatment and/or prophylaxis of one or more conditions or diseases
  • Epigenetic interaction differences on a chromosome are, generally speaking, structural differences which exist at a genomic level. The inventors have discovered that these differ between subsets (for example two, or two or more subsets) in a given population.
  • the invention therefore provides physicians with a method of personalizing medicine for the patient based on their epigenetic chromosome interactions, and provide an alternative more effective treatment and/or prophylaxis regime.
  • threshold levels for determining to what extent a subject is defined as belonging to one subgroup and not to a or the other subgroup of the population are applied.
  • said threshold may be measured by change in DAS28 (Disease Activity Score of 28 joints) score, in particular for rheumatoid arthritis.
  • a score above 1.2 units indicates a subject falls into the responder subgroup, whilst a score below 1.2 units indicates a subject is defined as a non-responder.
  • a subgroup will be at least 10%, at least 30%, at least 50% or at least 80% of the general population.
  • Certain embodiments of the invention utilise ligated nucleic acids, in particular ligated DNA. These comprise sequences from both of the regions that come together in a chromosome interaction and therefore provide information about the interaction.
  • the EpiSwitchTM method described herein, uses generation of such ligated nucleic acids to detect chromosome interactions.
  • One such method in particular one particular method of detecting chromosome interactions and/or one particular method of determining epigenetic chromosome interactions and/or one particular method of generating ligated nucleic acids (e.g. DNA), comprises the steps of:
  • Claim 1 of WO 2009/147386 A1 which can be used in those methods of the present invention which involve a ligated product(s) and/or a ligated nucleic acid(s), discloses a method of monitoring epigenetic changes comprising monitoring changes in conditional long range chromosomal interactions at at least one chromosomal locus where the spectrum of long range interaction is associated with a specific physiological condition, said method comprising the steps of:—
  • DNA loops indicates the presence of a specific long range chromosomal interaction.
  • PCR polymerase chain reaction
  • the size of the PCR product produced may be indicative of the specific chromosome interaction which is present, and may therefore be used to identify the status of the locus.
  • restriction enzymes which can be used to cut the DNA within the chromosomal locus of interest. It will be apparent that the particular enzyme used will depend upon the locus studied and the sequence of the DNA located therein.
  • a non-limiting example of a restriction enzyme which can be used to cut the DNA as described in the present invention is Taq I polymerase.
  • Embodiments Such as EpiSwitchTM Technology
  • the EpiSwitchTM Technology relates to the use of microarray EpiSwitchTM marker data in the detection of epigenetic chromosome conformation signatures specific for phenotypes.
  • the present inventors describe herein how the EpiSwitchTM Array Platform has been used for discovery of chromosome signature pool of potential biomarkers specific for particular disadvantageous phenotypes subgroups versus healthy controls.
  • the inventors also provide examples of validated use and translation of chromosome conformation signatures from microarray into PCR platform with examples of several markers specific between subgroups from the cohorts tested on the array.
  • Embodiments such as EpiSwitchTM which utilise ligated nucleic acids in the manner described herein (for identifying relevant chromosome interactions and in companion diagnostic methods) have several advantages. They have a low level of stochastic noise, for example because the nucleic acid sequences from the first set of nucleic acids of the present invention either hybridise or fail to hybridise with the second set of nucleic acids. This provides a binary result permitting a relatively simple way to measure a complex mechanism at the epigenetic level. EpiSwitchTM technology also has fast processing time and low cost. In one embodiment the processing time is 3 hours to 6 hours.
  • the sample will contain DNA from the individual. It will normally contain cells.
  • a sample is obtained by minimally invasive means, and may for example be blood. DNA may be extracted and cut up with standard restriction enzymes. This can pre-determine which chromosome conformations are retained and will be detected with the EpiSwitchTM platforms.
  • the sample is a blood sample previously obtained from the patient, the described method is advantageous because the procedure is minimally invasive. Due to the synchronisation of chromosome interactions between tissues and blood, including horizontal transfer, a blood sample can be used to detect the chromosome interactions in tissues, such as tissues relevant to disease. For certain conditions, such as cancer, genetic noise due to mutations can affect the chromosome interaction ‘signal’ in the relevant tissues and therefore using blood is advantageous.
  • nucleic acids are used in the companion diagnostic method and in other embodiments to detect the presence or absence of chromosome interactions (for example by binding to ligated nucleic acids generated from samples).
  • the nucleic acids of the invention typically comprise two portions each comprising sequence from one of the two regions of the chromosome which come together in the chromosome interaction. Typically each portion is at least 8, 10, 15, 20, 30 or 40 nucleotides in length.
  • Preferred nucleic acids comprise sequence from any of the genes mentioned in the tables, in particular where the nucleic acid is used in an embodiments relevant to the condition relevant for that table.
  • nucleic acids comprise the specific probe sequences mentioned in the tables for specific conditions or fragments or homologues of such sequences.
  • the nucleic acids are DNA. It is understood that where a specific sequence is provided the invention may use the complementary as required in the particular embodiment.
  • the second set of nucleic acid sequences has the function of being an index, and is essentially a set of nuclei acid sequences which are suitable for identifying subgroup specific sequence. They can represent the ‘background’ chromosomal interactions and might be selected in some way or be unselected. They are in general a subset of all possible chromosomal interactions.
  • the second set of nucleic acids may be derived by any suitable method. They can be derived computationally or they may be based on chromosome interaction in individuals. They typically represent a larger population group than the first set of nucleic acids. In one particular embodiment, the second set of nucleic acids represents all possible epigenetic chromosomal interactions in a specific set of genes. In another particular embodiment, the second set of nucleic acids represents a large proportion of all possible epigenetic chromosomal interactions present in a population described herein. In one particular embodiment, the second set of nucleic acids represent at least 50% or at least 80% of epigenetic chromosomal interactions in at least 20, 50, 100 or 500 genes.
  • the second set of nucleic acids typically represents at least 100 possible epigenetic chromosome interactions which modify, regulate or in any way mediate a disease state/phenotype in population.
  • the second set of nucleic acids may represent chromosome interactions that affect a diseases state in a species, for example comprising nucleic acids sequences which encode cytokines, kinases, or regulators associated with any disease state, predisposition to a disease or a disease phenotype.
  • the second set of nucleic acids comprises sequences representing epigenetic interactions relevant and not relevant to the companion diagnostic method.
  • the second set of nucleic acids derive at least partially from a naturally occurring sequences in a population, and are typically obtained by in silico methods. Said nucleic acids may further comprise single or multiple mutations in comparison to a corresponding portion of nucleic acids present in the naturally occurring nucleic acids. Mutations include deletions, substitutions and/or additions of one or more nucleotide base pairs.
  • the second set of nucleic acids may comprise sequence representing a homologue and/or orthologue with at least 70% sequence identity to the corresponding portion of nucleic acids present in the naturally occurring species. In another particular embodiment, at least 80% sequence identity or at least 90% sequence identity to the corresponding portion of nucleic acids present in the naturally occurring species is provided.
  • there are at least 100 different nucleic acid sequences in the second set of nucleic acids preferably at least 1000, 2000 or 5000 different nucleic acids sequences, with up to 100,000, 1,000,000 or 10,000,000 different nucleic acid sequences.
  • a typical number would be 100 to 1,000,000, such as 1,000 to 100,000 different nucleic acids sequences. All or at least 90% or at least 50% or these would correspond to different chromosomal interactions.
  • the second set of nucleic acids represent chromosome interactions in at least 20 different loci or genes, preferably at least 40 different loci or genes, and more preferably at least 100, at least 500, at least 1000 or at least 5000 different loci or genes, such as 100 to 10,000 different loci or genes.
  • the lengths of the second set of nucleic acids are suitable for them to specifically hybridise according to Watson Crick base pairing to the first set of nucleic acids to allow identification of chromosome interactions specific to subgroups.
  • the second set of nucleic acids will comprise two portions corresponding in sequence to the two chromosome regions which come together in the chromosome interaction.
  • the second set of nucleic acids typically comprise nucleic acid sequences which are at least 10, preferably 20, and preferably still 30 bases (nucleotides) in length.
  • the nucleic acid sequences may be at the most 500, preferably at most 100, and preferably still at most 50 base pairs in length.
  • the second set of nucleic acids comprise nucleic acid sequences of between 17 and 25 base pairs. In one embodiment at least 100, 80% or 50% of the second set of nucleic acid sequences have lengths as described above. Preferably the different nucleic acids do not have any overlapping sequences, for example at least 100%, 90%, 80% or 50% of the nucleic acids do not have the same sequence over at least 5 contiguous nucleotides.
  • the same set of second nucleic acids may be used with different sets of first nucleic acids which represent subgroups for different characteristics, i.e. the second set of nucleic acids may represent a ‘universal’ collection of nucleic acids which can be used to identify chromosome interactions relevant to different disease characteristics.
  • the first set of nucleic acids are normally from individuals known to be in two or more distinct subgroups defined by presence or absence of a characteristic relevant to a companion diagnostic, such as any such characteristic mentioned herein.
  • the first nucleic acids may have any of the characteristics and properties of the second set of nucleic acids mentioned herein.
  • the first set of nucleic acids is normally derived from a sample from the individual which has undergone treatment and processing as described herein, particularly the EpiSwitchTM cross-linking and cleaving steps.
  • the first set of nucleic acids represent all or at least 80% or 50% of the chromosome interactions present in the samples taken from the individuals.
  • the first set of nucleic acids represents a smaller population of chromosome interactions across the loci or genes represented by the second set of nucleic acids in comparison to the chromosome interactions represented by second set of nucleic acids, i.e. the second set of nucleic acids is representing a background or index set of interactions in a defined set of loci or genes.
  • the nucleic acids described herein may be in the form of a library which comprises at least 200, at least 500, at least 1000, at least 5000 or at least 10000 different nucleic acids from the second set of nucleic acids.
  • the invention provides a particular library of nucleic acids which typically comprises at least 200 different nucleic acids.
  • the library of nucleic acids may have any of the characteristics or properties of the second set of nucleic acids mentioned herein.
  • the library may be in the form of nucleic acids bound to an array.
  • the invention requires a means for allowing wholly or partially complementary nucleic acid sequences from the first set of nucleic acids and the second set of nucleic acids to hybridise.
  • all of the first set of nucleic acids is contacted with all of the second set of nucleic acids in a single assay, i.e. in a single hybridisation step.
  • any suitable assay can be used.
  • nucleic acids mentioned herein may be labelled, preferably using an independent label such as a fluorophore (fluorescent molecule) or radioactive label which assists detection of successful hybridisation. Certain labels can be detected under UV light.
  • an independent label such as a fluorophore (fluorescent molecule) or radioactive label which assists detection of successful hybridisation.
  • Certain labels can be detected under UV light.
  • the pattern of hybridisation represents differences in epigenetic chromosome interactions between the two subgroups, and thus provides a method of comparing epigenetic chromosome interactions and determination of which epigenetic chromosome interactions are specific to a subgroup in the population of the present invention.
  • pattern of hybridisation broadly covers the presence and absence of hybridisation between the first and second set of nucleic acids, i.e. which specific nucleic acids from the first set hybridise to which specific nucleic acids from the second set, and so it is not limited to any particular assay or technique, or the need to have a surface or array on which a ‘pattern’ can be detected.
  • the invention provides a companion diagnostic method based on information provided by chromosome interactions.
  • Two distinct companion diagnostic methods are provided which identify whether an individual has a particular characteristic relevant to a companion diagnostic.
  • One method is based on typing a locus in any suitable way and the other is based on detecting the presence or absence of chromosome interactions.
  • the characteristic may be any one of the characteristics mentioned herein relating to a condition.
  • the companion diagnostic method can be carried out at more than one time point, for example where monitoring of an individual is required.
  • the method of the invention which identified chromosome interactions that are specific to subgroups can be used to identify a locus, which may be a gene that can be typed as the basis of companion diagnostic test. Many different gene-related effects can lead to the same chromosome interaction occurring.
  • any characteristic of the locus may be typed, such as presence of a polymorphism in the locus or in an expressed nucleic acid or protein, the level of expression from the locus, the physical structure of the locus or the chromosome interactions present in the locus.
  • the locus may be any of the genes mentioned herein in the tables, in particular in Tables 1, 3, 5, 6c, 6E, 18a, 18b, 18c, 18d, 18e, 18f, 22, 23, 24 or 25 (in particular Tables 1, 3 and/or 5), or any property of a locus which is in the vicinity of a chromosome interaction found to be linked to the relevant condition.
  • the invention provides a companion diagnostic method which comprises detecting the presence or absence of chromosome interactions, typically 5 to 20 or 5 to 500 such interactions, preferably 20 to 300 or 50 to 100 interactions, in order to determine the presence or absence of a characteristic in an individual.
  • chromosome interactions are those in any of the genes mentioned herein.
  • the chromosome interactions which are typed are those represented by the nucleic acids disclosed in the tables herein, in particular in Tables 6b, 6D, 18b, 18e, 18f, 22, 23, 24 or 25 herein, for example when the method is for the purpose of determining the presence or absence of characteristics defined in those tables.
  • the companion diagnostic method can be used to detect the presence of any of the specific conditions or characteristics mentioned herein.
  • the companion diagnostic method can be used to detect responsiveness to methotrexate (or another rheumatoid arthritis drug) in rheumatoid arthritis patients, responsiveness to therapy for acute myeloid leukaemia (AML) patients, likelihood of relapse in melanoma, likelihood of developing prostate cancer and/or aggressive prostate cancer, and/or likelihood of developing beta-amyloid aggregate induced Alzheimer's disease.
  • methotrexate or another rheumatoid arthritis drug
  • AML acute myeloid leukaemia
  • the method of the invention detects responsiveness to immunotherapy, such as antibody therapy.
  • responsiveness to antibody therapy of cancer is detected, for example in immunotherapy using anti-PD-1 or anti-PD-L1 or a combined anti-PD-1/anti-PD-L1 therapy.
  • the cancer is melanoma, breast cancer, prostate cancer, acute myeloid leukaemia (AML), diffuse large B-cell lymphoma (DLBCL), pancreatic cancer, thyroid cancer, nasal cancer, liver cancer or lung cancer.
  • detection of chromosome interactions in STAT5B and/or IL15 are preferred, such as described in the Examples.
  • the work in the Examples is consistent with the fact that response to immunotherapy is a feature of the immune system epigenetic set up rather than cancer identity.
  • Anti-PD-1 is an antibody or antibody derivative or fragment that binds specifically to PD-1 (programmed cell death protein 1).
  • Anti-PD-L1 is an antibody or antibody derivative or fragment that binds specifically to PD-L1 protein which is a ligand of PD-1.
  • the method(s) and/or companion diagnostic method of the invention can be used to:
  • the presence or absence of any of the chromosome interactions within any of the relevant genes mentioned in the tables are detected.
  • the presence or absence of chromosome interactions represented by the probes sequences in the Tables is determined in the method.
  • the individual to be tested may or may not have any symptoms of any disease condition or characteristic mentioned herein.
  • the individual may be at risk of any such condition or characteristic.
  • the individual may have recovered or be in the process of recovering from the condition or characteristic.
  • the individual is preferably a mammal, such as a non-human primate, human or rodent.
  • the individual may be male or female.
  • the individual may be 30 years old or older.
  • the individual may be 29 years old or younger.
  • the invention provides a method of identifying an agent which is capable of changing the disease state of an individual from a first state to a second state comprising determining whether a candidate agent is capable of changing the chromosomal interactions from those corresponding with the first state to chromosomal interactions which correspond to the second state, wherein preferably the first and second state correspond to presence or absence of:
  • the method determines whether a candidate agent is capable of changing any chromosomal interaction mentioned herein.
  • the method may be carried out in vitro (inside or outside a cell) or in vivo (upon a non-human organism).
  • the method is carried out on a cell, cell culture, cell extract, tissue, organ or organism, such as one which comprises the relevant chromosome interaction(s).
  • the cell is The method is typically carried out by contacting (or administering) the candidate agent with the gene, cell, cell culture, cell extract, tissue, organ or organism.
  • Suitable candidate substances which tested in the above screening methods include antibody agents (for example, monoclonal and polyclonal antibodies, single chain antibodies, chimeric antibodies and CDR-grafted antibodies). Furthermore, combinatorial libraries, defined chemical identities, peptide and peptide mimetics, oligonucleotides and natural agent libraries, such as display libraries (e.g. phage display libraries) may also be tested.
  • the candidate substances may be chemical compounds, which are typically derived from synthesis around small molecules which may have any of the properties of the agent mentioned herein.
  • genes and chromosome interactions are mentioned in the tables.
  • genes and chromosome interactions are provided in the tables.
  • the methods chromosome interactions are detected from at least 1, 3, 10, 20, 30 or 50 of the relevant genes listed in the table.
  • the presence or absence of at least 1, 3, 10, 20, 30 or 50 of the relevant specific chromosome interactions represented by the probe sequences in any one table is detected.
  • the loci may be upstream or downstream of any of the genes mentioned herein, for example 50 kb upstream or 20 kb downstream.
  • each condition the presence or absence of at least 1, 3, 5, 10, 20 of the relevant specific chromosome interactions represented by the top range of p-values or adjusted p-values shown in Table 48 are detected. In another embodiment for each condition the presence or absence of at least 1, 3, 5, 10, 20, 30 or 50 of the relevant specific chromosome interactions represented by the mid range of p-values or adjusted p-values shown in Table 48 are detected. In yet another embodiment for each condition the presence or absence of at least 1, 3, 5, 10, 20, 30 or 50 of the relevant specific chromosome interactions represented by the bottom range of p-values or adjusted p-values shown in Table 48 are detected.
  • each condition the presence or absence of at least 1, 2, 3, 5 or 10 of the relevant specific chromosome interactions from each of the top, mid and bottom ranges of p-values or adjusted p-values shown in Table 48 are detected, i.e. at least 3, 6, 9, 18 or 30 in total.
  • chromosome interactions can be detected (i.e. determining the presence of absence of), which typically represent all of the interactions disclosed in a table herein or a selection from a table.
  • particular numbers of interactions can be selected from individual tables. In one embodiment at least 10%, 20%, 30%, 50%, 70% or 90% of the interactions disclosed in any table, or disclosed in relation to any condition, are detected.
  • the interactions which are detected may correspond to presence or absence of a particular characteristic, for example as defined herein, such as in any table herein. If a combination of interactions are detected then they may all correspond with presence of the characteristic or they may all correspond to absence of the characteristic. In one embodiment the combination of interactions which is detected corresponds to at least 2, 5 or 10 interactions which relate to presence of the characteristic and at least 2, 5 or 10 other interactions that relate to absence of the characteristic.
  • the probe shown in table 49 may be part of or combined with any of the selections mentioned herein, particularly for conditions relating to cancer, and responsiveness to therapy, such as anti-PD1 therapy.
  • the methods of the invention can be carried out to detect chromosome interactions relevant to or impacted by a genetic modification, i.e. the subgroups may differ in respect to the genetic modification.
  • the modification might be of entire (non-human) organisms or parts of organisms, such as cells.
  • the first set of nucleic acids may be from at least two subgroups, one of which has a defined genetic modification and one which does not have the genetic modification, and the method may determine which chromosomal interactions are relevant to, and/or affected by, the genetic modification.
  • the modification may be achieved by any suitable means, including CRISPR technology.
  • the invention includes a method of determining whether a genetic modification to the sequence at a first locus of a genome affects other loci of the genome comprising detecting chromosome signatures at one or more other loci after the genetic modification is made, wherein preferably the genetic modification changes system characteristics, wherein said system is preferably the metabolic system, the immune system, the endocrine system, the digestive system, integumentary system, the skeletal system, the muscular system, the lymphatic system, the respiratory system, the nervous system, or the reproductive system.
  • Said detecting chromosome signatures optionally comprises detecting the presence or absence of 5 or more (e.g. 5) different chromosomal interactions, preferably at 5 or more (e.g. 5) different loci, preferably as defined in any of the Tables.
  • the chromosomal signatures or interactions are identified by any suitable method mentioned herein.
  • the genetic modification is achieved by a method comprising introducing into a cell (a) two or more RNA-guided endonucleases or nucleic acid encoding two or more RNA-guided endonucleases and (b) two or more guiding RNAs or DNA encoding two or more guiding RNAs, wherein each guiding RNA guides one of the RNA-guided endonucleases to a targeted site in the chromosomal sequence and the RNA-guided endonuclease cleaves at least one strand of the chromosomal sequence at the targeted site.
  • the modification is achieved by a method of altering expression of at least one gene product comprising introducing into a eukaryotic cell containing and expressing a DNA molecule having a target sequence and encoding the gene product an engineered, non-naturally occurring Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-CRISPR associated (Cas) (CRISPR-Cas) system comprising one or more vectors comprising:
  • each RNA-guided endonuclease is derived from a Cas9 protein and comprises at least two nuclease domains, and optionally wherein one of the nuclease domains of each of the two RNA-guided endonucleases is modified such that each RNA-guided endonuclease cleaves one strand of a double-stranded sequence, and wherein the two RNA-guided endonucleases together introduce a double-stranded break in the chromosomal sequence that is repaired by a DNA repair process such that the chromosomal sequence is modified.
  • the modification comprised a deletion, insertion or substitution of at least 5, 20, 50, 100 or 1000 bases, preferably up 10,000 or 1000,000 bases.
  • the modification may be at any of the loci mentioned herein, for example in any of the regions or genes mentioned in any of the tables.
  • the chromosomal interactions which are detected at other (non-modified) loci may also be in any of the loci mentioned herein, for example in any of the regions or genes mentioned in any of the tables.
  • Embodiments relating to genetic modifications many be performed on any organism, including eukaryotes, chordates, mammals, plants, agricultural animals and plants, and non-human organisms.
  • the method of the invention can be described in different ways. It can be described as a method of making a ligated nucleic acid comprising (i) in vitro cross-linking of chromosome regions which have come together in a chromosome interaction; (ii) subjecting said cross-linked DNA to cutting or restriction digestion cleavage; and (iii) ligating said cross-linked cleaved DNA ends to form a ligated nucleic acid, wherein detection of the ligated nucleic acid may be used to determine the chromosome state at a locus, and wherein preferably:
  • the method of the invention can be described as a method for detecting chromosome states which represent different subgroups in a population comprising determining whether a chromosome interaction is present or absent within a defined region of the genome, wherein preferably:
  • the invention includes detecting chromosome interactions at any locus, gene or regions mentioned herein.
  • the invention includes use of the nucleic acids and probes (or primers) mentioned herein to detect chromosome interactions, for example use of at least 10, 50, 100 or 500 such nucleic acids or probes to detect chromosome interactions in at least 10, 20, 100 or 500 different loci or genes.
  • Probe EpiswitchTM marker
  • gene data representing chromosome interactions present in a condition (the first mentioned group) and absent in a control group, typically but not necessarily healthy individuals (the second mentioned group).
  • the probe sequences show sequence which can be used to detect a ligated product generated from both sites of gene regions that have come together in chromosome interactions, i.e. the probe will comprise sequence which is complementary to sequence in the ligated product.
  • the first two sets of Start-End positions show probe positions, and the second two sets of Start-End positions show the relevant 4 kb region. The following information is provided in the probe data table:
  • the gene table data shows genes where a relevant chromosome interaction has been found to occur.
  • the p-value in the loci table is the same as the HyperG_Stats (p-value for the probability of finding that number of significant EpiSwitchTM markers in the locus based on the parameters of hypergeometric enrichment).
  • the probes are designed to be 30 bp away from the Taq1 site.
  • PCR primers are also designed to detect ligated product but their locations from the Taq1 site vary.
  • End 2 30 bases downstream of TaqI site on fragment 2
  • End 2 4000 bases downstream of TaqI site on fragment 2
  • the sample will contain at least 2 ⁇ 10 5 cells.
  • the sample may contain up to 5 ⁇ 10 5 cells. In one embodiment, the sample will contain 2 ⁇ 10 5 to 5.5 ⁇ 10 5 cells
  • Crosslinking of epigenetic chromosomal interactions present at the chromosomal locus is described herein. This may be performed before cell lysis takes place. Cell lysis may be performed for 3 to 7 minutes, such as 4 to 6 or about 5 minutes. In some embodiments, cell lysis is performed for at least 5 minutes and for less than 10 minutes.
  • DNA restriction is performed at about 55° C. to about 70° C., such as for about 65° C., for a period of about 10 to 30 minutes, such as about 20 minutes.
  • a frequent cutter restriction enzyme is used which results in fragments of ligated DNA with an average fragment size up to 4000 base pair.
  • the restriction enzyme results in fragments of ligated DNA have an average fragment size of about 200 to 300 base pairs, such as about 256 base pairs.
  • the typical fragment size is from 200 base pairs to 4,000 base pairs, such as 400 to 2,000 or 500 to 1,000 base pairs.
  • a DNA precipitation step is not performed between the DNA restriction digest step and the DNA ligation step.
  • DNA ligation is described herein. Typically the DNA ligation is performed for 5 to 30 minutes, such as about 10 minutes.
  • the protein in the sample may be digested enzymatically, for example using a proteinase, optionally Proteinase K.
  • the protein may be enzymatically digested for a period of about 30 minutes to 1 hour, for example for about 45 minutes.
  • PCR detection is capable of detecting a single copy of the ligated nucleic acid, preferably with a binary read-out for presence/absence of the ligated nucleic acid.
  • homologues of polynucleotide/nucleic acid are referred to herein.
  • Such homologues typically have at least 70% homology, preferably at least 80%, at least 85%, at least 90%, at least 95%, at least 97%, at least 98% or at least 99% homology, for example over a region of at least 10, 15, 20, 30, 100 or more contiguous nucleotides, or across the portion of the nucleic acid which is from the region of the chromosome involved in the chromosome interaction.
  • the homology may be calculated on the basis of nucleotide identity (sometimes referred to as “hard homology”).
  • homologues of polynucleotide/nucleic acid (e.g. DNA) sequences are referred to herein by reference to % sequence identity.
  • homologues typically have at least 70% sequence identity, preferably at least 80%, at least 85%, at least 90%, at least 95%, at least 97%, at least 98% or at least 99% sequence identity, for example over a region of at least 10, 15, 20, 30, 100 or more contiguous nucleotides, or across the portion of the nucleic acid which is from the region of the chromosome involved in the chromosome interaction.
  • the UWGCG Package provides the BESTFIT program which can be used to calculate homology and/or % sequence identity (for example used on its default settings) (Devereux et al (1984) Nucleic Acids Research 12, p 387-395).
  • the PILEUP and BLAST algorithms can be used to calculate homology and/or % sequence identity and/or line up sequences (such as identifying equivalent or corresponding sequences (typically on their default settings), for example as described in Altschul S. F. (1993) J Mol Evol 36:290-300; Altschul, S, F et al (1990) J Mol Biol 215:403-10.
  • HSPs high scoring sequence pair
  • Extensions for the word hits in each direction are halted when: the cumulative alignment score falls off by the quantity X from its maximum achieved value; the cumulative score goes to zero or below, due to the accumulation of one or more negative-scoring residue alignments; or the end of either sequence is reached.
  • the BLAST algorithm parameters W5 T and X determine the sensitivity and speed of the alignment.
  • the BLAST algorithm performs a statistical analysis of the similarity between two sequences; see e.g., Karlin and Altschul (1993) Proc. Natl. Acad. Sci. USA 90: 5873-5787.
  • One measure of similarity provided by the BLAST algorithm is the smallest sum probability (P(N)), which provides an indication of the probability by which a match between two polynucleotide sequences would occur by chance.
  • P(N) the smallest sum probability
  • a sequence is considered similar to another sequence if the smallest sum probability in comparison of the first sequence to the second sequence is less than about 1, preferably less than about 0.1, more preferably less than about 0.01, and most preferably less than about 0.001.
  • the homologous sequence typically differs by 1, 2, 3, 4 or more bases, such as less than 10, 15 or 20 bases (which may be substitutions, deletions or insertions of nucleotides). These changes may be measured across any of the regions mentioned above in relation to calculating homology and/or % sequence identity.
  • the second set of nucleic acids may be bound to an array, and in one embodiment there are at least 15,000, 45,000, 100,000 or 250,000 different second nucleic acids bound to the array, which preferably represent at least 300, 900, 2000 or 5000 loci. In one embodiment one, or more, or all of the different populations of second nucleic acids are bound to more than one distinct region of the array, in effect repeated on the array allowing for error detection.
  • the array be based on an Agilent SurePrint G3 Custom CGH microarray platform. Detection of binding of first nucleic acids to the array may be performed by a dual colour system.
  • Therapeutic agents are mentioned herein.
  • the invention provides such agents for use in preventing or treating the relevant condition. This may comprise administering to an individual in need a therapeutically effective amount of the agent.
  • the invention provides use of the agent in the manufacture of a medicament to prevent or treat the disease.
  • the methods of the invention may be used to select an individual for treatment.
  • the methods of the invention, and in particular the companion diagnostic assay method may include a treatment step where a person identified by the method may then be administered with an agent that prevents or treats the relevant condition.
  • the formulation of the agent will depend upon the nature of the agent.
  • the agent will be provided in the form of a pharmaceutical composition containing the agent and a pharmaceutically acceptable carrier or diluent. Suitable carriers and diluents include isotonic saline solutions, for example phosphate-buffered saline. Typical oral dosage compositions include tablets, capsules, liquid solutions and liquid suspensions.
  • the agent may be formulated for parenteral, intravenous, intramuscular, subcutaneous, transdermal or oral administration.
  • the dose of agent may be determined according to various parameters, especially according to the substance used; the age, weight and condition of the individual to be treated; the route of administration; and the required regimen. A physician will be able to determine the required route of administration and dosage for any particular agent.
  • a suitable dose may however be from 0.1 to 100 mg/kg body weight such as 1 to 40 mg/kg body weight, for example, to be taken from 1 to 3 times daily.
  • nucleic acids or therapeutic agents may be in purified or isolated form.
  • The may be in a form which is different from that found in nature, for example they may be present in combination with other substance with which they do not occur in nature.
  • the nucleic acids (including portions of sequences defined herein) may have sequences which are different to those found in nature, for example having at least 1, 2, 3, 4 or more nucleotide changes in the sequence as described in the section on homology.
  • the nucleic acids may have heterologous sequence at the 5′ or 3′ end.
  • the nucleic acids may be chemically different from those found in nature, for example they may be modified in some way, but preferably are still capable of Watson-Crick base pairing.
  • nucleic acids will be provided in double stranded or single stranded form.
  • the invention provides all the of specific nucleic acid sequences mentioned herein in single or double stranded form, and thus includes the complementary strand to any sequence which is disclosed.
  • the invention also provides a kit for carrying out any method of the invention, including detection of a chromosomal interaction associated with a particular subgroup.
  • a kit can include a specific binding agent capable of detecting the relevant chromosomal interaction, such as agents capable of detecting a ligated nucleic acid generated by processes of the invention.
  • Preferred agents present in the kit include probes capable of hybridising to the ligated nucleic acid or primer pairs, for example as described herein, capable of amplifying the ligated nucleic acid in a PCR reaction.
  • the invention also provides a device that is capable of detecting the relevant chromosome interactions.
  • the device preferably comprises any specific binding agents, probe or primer pair capable of detecting the chromosome interaction, such as any such agent, probe or primer pair described herein.
  • Treatments for MPNST include surgery, radiotherapy and chemotherapy.
  • the EpiSwitchTM platform technology detects epigenetic regulatory signatures of regulatory changes between normal and abnormal conditions at loci.
  • the EpiSwitchTM platform identifies and monitors the fundamental epigenetic level of gene regulation associated with regulatory high order structures of human chromosomes also known as chromosome conformation signatures.
  • Chromosome signatures are a distinct primary step in a cascade of gene deregulation. They are high order biomarkers with a unique set of advantages against biomarker platforms that utilize late epigenetic and gene expression biomarkers, such as DNA methylation and RNA profiling.
  • the custom EpiSwitchTM array-screening platforms come in 4 densities of, 15K, 45K, 100K, and 250K unique chromosome conformations, each chimeric fragment is repeated on the arrays 4 times, making the effective densities 60K, 180K, 400K and 1 Million respectively.
  • the 15K EpiSwitchTM array can screen the whole genome including around 300 loci interrogated with the EpiSwitchTM Biomarker discovery technology.
  • the EpiSwitchTM array is built on the Agilent SurePrint G3 Custom CGH microarray platform; this technology offers 4 densities, 60K, 180K, 400K and 1 Million probes.
  • the density per array is reduced to 15K, 45K, 100K and 250K as each EpiSwitchTM probe is presented as a quadruplicate, thus allowing for statistical evaluation of the reproducibility.
  • the average number of potential EpiSwitchTM markers interrogated per genetic loci is 50; as such the numbers of loci that can be investigated are 300, 900, 2000, and 5000.
  • the EpiSwitchTM array is a dual colour system with one set of samples, after EpiSwitchTM library generation, labelled in Cy5 and the other of sample (controls) to be compared/analyzed labelled in Cy3.
  • the arrays are scanned using the Agilent SureScan Scanner and the resultant features extracted using the Agilent Feature Extraction software.
  • the data is then processed using the EpiSwitchTM array processing scripts in R.
  • the arrays are processed using standard dual colour packages in Bioconductor in R: Limma*.
  • the normalisation of the arrays is done using the normalised within Arrays function in Limma* and this is done to the on chip Agilent positive controls and EpiSwitchTM positive controls.
  • the data is filtered based on the Agilent Flag calls, the Agilent control probes are removed and the technical replicate probes are averaged, in order for them to be analysed using Limma*.
  • LIMMA is Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments.
  • Limma is a R package for the analysis of gene expression data arising from microarray or RNA-Seq.
  • the pool of probes is initially selected based on adjusted p-value, FC and CV ⁇ 30% (arbitrary cut off point) parameters for final picking. Further analyses and the final list are drawn based only on the first two parameters (adj p-value; FC).
  • EpiSwitchTM screening arrays are processed using the EpiSwitchTM Analytical Package in R in order to select high value EpiSwitchTM markers for translation on to the EpiSwitchTM PCR platform.
  • Probes are selected based on their corrected p-value (False Discovery Rate, FDR), which is the product of a modified linear regression model. Probes below p-value
  • the top 40 markers from the statistical lists are selected based on their ER for selection as markers for PCR translation.
  • the top 20 markers with the highest negative ER load and the top 20 markers with the highest positive ER load form the list.
  • the resultant markers from step 1 the statistically significant probes form the bases of enrichment analysis using hypergeometric enrichment (HE).
  • HE hypergeometric enrichment
  • the statistical probes are processed by HE to determine which genetic locations have an enrichment of statistically significant probes, indicating which genetic locations are hubs of epigenetic difference.
  • the most significant enriched loci based on a corrected p-value are selected for probe list generation. Genetic locations below p-value of 0.3 or 0.2 are selected. The statistical probes mapping to these genetic locations, with the markers from step 2, form the high value markers for EpiSwitchTM PCR translation.
  • Example 1 A Method of Determining the Chromosome Interactions which are Relevant to a Companion Diagnostic that Distinguishes Between Non-Responders and Responders of Methotrexate for the Treatment of Rheumatoid Arthritis
  • Stable epigenetic profiles of individual patients modulate sensitivity of signalling pathways, regulate gene expression, influence the paths of disease development, and can render ineffective the regulatory controls responsible for effective action of the drug and response to treatment.
  • epigenetic profiles of rheumatoid arthritis (RA) patients in order to evaluate its role in defining the non-responders to Methotrexate (MTX) treatment.
  • DMARDs first-line disease modifying anti-rheumatic drugs
  • MTX methotrexate
  • MTX methotrexate
  • ERA early rheumatoid arthritis
  • first line DMARDs in particular, methotrexate (MTX)
  • MTX methotrexate
  • the capacity to classify drug na ⁇ ve patients into those that will not respond to first line DMARDs would be an invaluable tool for patient stratification.
  • chromosome conformational signatures highly informative and stable epigenetic modifications that have not previously been described in RA
  • PBMCs Peripheral blood mononuclear cells
  • MTX responsiveness was defined at 6 months using the following criteria: Responders—DAS28 remission (DAS28 ⁇ 2.6) or a good response (DAS28 improvement of >1.2 and DAS28 3.2). Non-responders—no improvement in DAS28 (50.6).
  • CCS chromosome conformational signatures
  • Differentiating CCS were defined by LIMMA* linear modeling, subsequent binary filtering and cluster analysis.
  • a validation cohort of 30 MTX responders and 30 non-responders were screened for the differentiating CCS using the EpiSwitchTM PCR platform.
  • the differentiating signature was further refined using binary scores and logistical regression modeling, and the accuracy and robustness of the model determined by ROC analysis**.
  • LIMMA is Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments.
  • Limma is a R package for the analysis of gene expression data arising from microarray or RNA-Seq.
  • ROC Receiver Operating Characteristic and refers to ROC curves.
  • An ROC curve is a graphical plot that illustrates the performance of a binary classifier system as its discrimination threshold is varied. The curve is created by plotting the true positive rate against the false positive rate at various threshold settings.
  • CCS Chromosome Conformation Signatures
  • this stratification model had a predictive power of sensitivity at 92% for NR to MTX.
  • This epigenetic RA biomarker signature can distinguish between ERA and healthy controls (HC).
  • This combinatorial, predictive peripheral blood signature can support earlier introduction of more aggressive therapeutics in the clinic, paving the way towards personalized medicine in RA.
  • RA is a chronic autoimmune disease affecting up to 1% of the global population.
  • Pathogenesis is multifactorial and characterized by primarily immune host gene loci interacting with environmental factors, particularly smoking and other pulmonary stimuli.
  • the exposure of a genetically susceptible individual to such environmental factors suggests an epigenetic context for disease onset and progression.
  • chromatin markers e.g. methylation status of the genome
  • MTX 8 the commonest first-choice medication recommended by EULAR (The European League against Rheumatism) and ACR (American College of Rheumatology) management guidelines, delivers clinically meaningful response rates ranging from 50 to 65% after 6 months of treatment. Such responses, and especially the rather smaller proportion that exhibits high hurdle responses, cannot currently be predicted in an individual patient. This begets a ‘trial and error’ based approach to therapeutic regimen choice (mono or combinatorial therapeutics). The ability to predict drug responsiveness in an individual patient would be an invaluable clinical tool, given that response to first-line treatment is the most significant predictor of long-term outcome.
  • CCS 13,322 chromosome conformation signatures
  • Identified epigenetic profiles of na ⁇ ve RA patients were subject to statistical analysis using GraphPad Prism, WEKA and R Statistical language.
  • EpiSwitchTM platform and extended cohort of 90 clinical samples we have identified a pool of over 922 epigenetic lead biomarkers, statistically significant for responders, non-responders, RA patients and healthy controls.
  • 123 genetic loci (Table 1) associated with RA pathogenesis were selected and annotated with chromosome conformations interactions predicted using the EpiSwitchTM in silico prediction package.
  • the EpiSwitchTM in silico prediction generated 13,322 high-confidence CCS marker candidates (Table 1). These candidates were used to generate a bespoke discovery EpiSwitchTM array ( FIG. 5 ) to screen peripheral blood mononuclear cells isolated at the time of diagnosis (DMARD-na ⁇ ve) from 4 MTX responders (R) and 4 MTX NR, all clinically defined after 6 months therapy ( FIG. 1A , B and Table 2), and 4 healthy controls (HC).
  • a LIMMA* linear model of the normalized epigenetic load was employed. A total of 922 statistically significant stratifying markers (significance assessed on the basis of adjusted p value and EpiSwitchTM Ratio) were identified. Of the 922 lead markers, 420 were associated with NR, 210 with R and 159 with HC ( FIG. 1C ). Binary filtering and cluster analysis was applied to the EpiSwitchTM markers to assess the significance of CCS identified.
  • a stepwise hierarchical clustering approach (using Manhattan distance measure with complete linkage agglomeration and taking into account R vs NR, HC vs R & HC vs NR) reduced the number of significant markers from 922 to 65 and finally resulted in a 30-marker stratifying profile ( FIG. 1D and Table 3).
  • LIMMA is Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments.
  • Limma is a R package for the analysis of gene expression data arising from microarray or RNA-Seq.
  • the 30 identified markers were screened in a second ERA patient cohort of R and NR ( FIG. 2A , B and Table 4) in a stepwise approach, using the EpiSwitchTM PCR platform ( FIG. 5 ).
  • the entire 30 CCS markers were run in 12 ERA patients (6 R and 6 NR).
  • the best differentiating CCS markers were identified by applying a Chi-squared test for independence with Yate's continuity correction on the binary scores, revealing a 12-marker CCS profile (Table 5).
  • These 12 CCS markers were run on an additional 12 ERA patients (6 R and 6 NR) and the data combined with the previous 12 ERA.
  • composition of the stratifying signature identifies the location of chromosomal conformations that potentially control genetic locations of primary importance for determining MTX response.
  • Principal component analysis (PCA) of the binary scores for the classifying 5 EpiSwitchTM CCS markers provided clear separation of ERA patients based on their MTX response ( FIG. 2D ).
  • the cut-off values were set at 50.30 for responders and 20.70 for non-responders.
  • the score of 50.30 had a true positive rate of 92% (95% confidence interval [95% CI] 75-99%) whilst a score of 20.70 had a true negative response rate of 93% (95% CI 76-99%).
  • the number of observed and predicted patients per response category (R or NR to MTX) is shown in Table 6. With the EpiSwitchTM CCS marker model, 53 patients (88%) were classified as either responder or non-responder.
  • the average model accuracy statistics were adjusted for population R/NR to MTX using Bayes prevalence theorem 21 .
  • PPV positive predictive value
  • NPV negative predictive value
  • ROC Receiver Operating Characteristic and refers to ROC curves.
  • An ROC curve is a graphical plot that illustrates the performance of a binary classifier system as its discrimination threshold is varied. The curve is created by plotting the true positive rate against the false positive rate at various threshold settings.
  • Example 1 Table 6D and 6E—Stratifying Between RA-MTX Responders and Non-Responders
  • ERA patients in this study are part of the Scottish early rheumatoid arthritis (SERA) inception cohort. Demographic, clinical and immunological factors were obtained at diagnosis and 6 months (Table 1). Inclusion in the inception cohort was based on clinical diagnosis of undifferentiated polyarthritis or RA ( ⁇ 1 swollen joint) at a secondary care rheumatology unit in Scotland. Exclusion criteria were previous or current DMARD/biological therapy and/or established alternative diagnosis (i.e. psoriatic arthritis, reactive arthritis). Inclusion in this study was based on a diagnosis of RA (fulfilled the 2010 ACR/EULAR criteria for RA) with moderate to high disease activity (DAS28 ⁇ 3.2) and subsequent monotherapy with MTX.
  • SERA Scottish early rheumatoid arthritis
  • Pattern recognition methodology was used to analyse human genome data in relation to the transcriptional units in the human genome.
  • the proprietary EpiSwitchTM pattern recognition software 18, 20 provides a probabilistic score that a region is involved in chromatin interaction. Sequences from 123 gene loci were downloaded and processed to generate a list of the 13,322 most probable chromosomal interactions. 60mer probes were designed to interrogate these potential interactions and uploaded as a custom array to the Agilent SureDesign website. Sequence-specific oligonucleotides were designed using Primer3 23 , at the chosen sites for screening potential markers by nested PCR. Oligonucleotides were tested for specificity using oligonucleotide specific BLAST.
  • Each array contains 55088 probes spots, representing 13,322 potential chromosomal interactions predicted by the EpiSwitchTM pattern recognition software quadruplicated, plus EpiSwitchTM and Agilent controls. Briefly, 1 ⁇ g of EpiSwitchTM template was labelled using the Agilent SureTag labelling kit. Processing of labelled DNA was performed. Array analysis was performed immediately after washing using the Agilent scanner and software. In order to compare all the experiments the data was background corrected and normalized. Since each spot in the array is present in quadruplicate, the median of the four spots of each probe in the array was calculated and its log 2 transformed value was used for further analysis. The coefficient of variation and p-value was calculated for each probe replicate.
  • EpiSwitchTM PCR detection Oligonucleotides were tested on template to confirm that each primer set was working correctly. To accommodate for technical and replicate variations, each sample was processed four times. All the extracts from these four replicates were pooled and the final nested PCR was performed on each sample. This procedure permitted the detection of limited copy-number templates with higher accuracy. All PCR amplified samples were visualised by electrophoresis in the LabChip* GX from Perkin Elmer, using the LabChip DNA 1K Version2 kit (Perkin Elmer) and internal DNA marker was loaded on the DNA chip according to the manufacturer's protocol using fluorescent dyes. Fluorescence was detected by laser and electropherogram read-outs translated into a simulated band on gel picture using the instrument software. The threshold we set for a band to be deemed positive was 30 fluorescence units and above.
  • Example 1 Example 1 - Table 2. Patient Characteristics - Discovery Cohort Baseline 6 months Healthy Non-responder Responder P value Non-responder Responder P value control Age - years 55 ⁇ 6.1 55 ⁇ 19.7 >0.99 — — — 52 ⁇ 13.3 Males - no. (%) 1 (25) 1 (25) 1 — — — 3 (38) Caucasian - no.
  • Example 1 Table 4. Patient characteristics-Validation Cohort Baseline 6 months Non- P Non- Healthy Responder responder value Responder responder P value control Age - years 58 ⁇ 14.5 54 ⁇ 13.2 0.26 — — — 45 ⁇ 15.4 Males - no. (%) 10 (33) 13 (43) 0.6 — — — 11 (37) Caucasian - no.
  • Example 1A RA Analysis: MTX Responders Vs Non-Responders: Work Subsequent to Example 1
  • Example 1A a biostatistical hypergeometric analysis was carried out, using the “Statistical Pipeline” method(s) at the beginning of the Examples section in the present specification, to generate further refined DNA probes stratifying between MTX responders vs MTX non-responders, for RA patients on MTX monotherapy.
  • Table 6b (and continuation part Table 6c) hereinafter discloses Probe and Loci data for RA-MTX—DNA probes stratifying between responders (R) and non-responders (NR).
  • B B-statistic (lods or B), which is the log-odds that that gene is differentially expressed.
  • FC is the non-log Fold Change.
  • FC_1 is the non-log Fold Change centred around zero. It is seen that Table 6b+6c includes the sequences of 25 refined preferable DNA probes (60mers) for identifying MTX responders (MTX-R), and of 24 refined preferable DNA probes (60mers) for identifying MTX responders (MTX-NR), from the hypergeometric analysis.
  • Loop FC FC 1 LS detected 60 mer 0.5774097 -1.7318725 -1 MTX-R TGTTTTTTGGCTGCATAAATGTCTTCTTTCGAAATAATCATCAAAATATTTTTCATTGAC (SEQ ID NO:1) 0.6052669 -1.6521636 -1 MTX-R CACCCCCATCTCCCTTTGCTGACTCTCTTCGATGAATCCATTTTTTTGGAAATAGATGAT (SEQ ID NO:2) 0.6567507 -1.5226477 -1 MTX-R CACCCCCATCTCCCTTTGCTGACTCTCTTCGAACTGTGGCAATTTTAACTTTTCAAATTG (SEQ ID NO:3) 0.6624775 -1.5094851 -1 MTX-R CACCCCCATCTCCCTTTGCTGACTCTCTTCGAGGCATGATTTGAGTCTTGACAGAAGTTC
  • NR_R_adj.P Probe sequence Probes Value Val 60 mer TNFRSF14_Site4_Site1_FR 0.001232118 0.079419805 TGATCACTGTTTCCTATGAGGATACAGCTCGAGGGGCA GGGGGCGGTCCTGGGCCAGGCG (SEQ ID NO: 50) TNFRSF14_Site4_Site1_RR 0.002061691 0.082014717 AACCTGGAGAACGCCAAGCGCTTCGCCATCGAGGGGCA GGGGGCGGTCCTGGGCCAGGCG (SEQ ID NO: 51) TNFRSF1A_Site2_Site5_FR 0.004469941 0.093849223 CTACCTTTGTGGCACTTGGTACAGCAAATCGACGGGCC CCGTGAGGCGGGCGGGACCC (SEQ ID NO: 53) TNFRSF1A_Site1_Site5_FR 0.00
  • Example 2 A Method of Determining the Chromosome Interactions Relevant to a Companion Diagnostic as Pharmacodynamic Biomarker During the Inhibition of LSD1 in the Treatment of AML (Acute Myeloid Leukemia)
  • Pharmacodynamic (PD) biomarkers are molecular indicators of drug effect on the target in an organism.
  • a PD biomarker can be used to examine the link between drug regimen, target effect, and biological tumour response. Coupling new drug development with focused PD biomarker measurements provides critical data to make informed, early go/no-go decisions, to select rational combinations of targeted agents, and to optimise schedules of combination drug regimens. Use of PD endpoints also enhances the rationality and hypothesis-testing power throughout drug development, from selection of lead compounds in preclinical models to first-in-human trials (National Cancer Institute).
  • chromosome signatures could be used as pharmacodynamic biomarkers to monitor response to a number of drugs at time points consistent with phenotypic changes observed.
  • BET inhibition causes the transcriptional repression of key oncogenes BCL2, CDK6, and C-MYC BET inhibitors like LSD1 inhibitors are epigenetic therapies, targeting the acetylated and methylation states of histones.
  • BCL2 key oncogenes
  • CDK6 and C-MYC BET inhibitors like LSD1 inhibitors
  • LSD1 inhibitors are epigenetic therapies, targeting the acetylated and methylation states of histones.
  • the findings at the MYC locus with EpiSwitchTM show evidence of regulatory change with LSD1 inhibition.
  • MV4-11 cell line harbours translocations that express MLL-AF4 and FLT3-ITD whereas THP-1 only expresses MLL-AF9.
  • Epigenetic biomarkers identified by EpiSwitchTM platform are well suited for delineating epigenetic mechanisms of LSD1 demethylase and for stratification of different specificities of LSD1 inhibitors within and between cell lines. This work demonstrates that chromosome conformation signatures could be used as mechanism-linked predictive biomarkers in LSD1 inhibition.
  • a standard LSD1 inhibitor is investigated in this study, tranylcypromine (TCP).
  • THP-1 tranylcypromine
  • MV4-11 tranylcypromine
  • Table 7 Chromosome signatures identified in the vicinity of MYD88 gene in THP-1 cells are shown in Table 7.
  • Chromosome signatures identified in the vicinity of MYD88 gene in MV4-11 cells are shown in Table 8.
  • Table 8 Each number combination, points to individual chromosome interaction. The positions across the gene have been created and selected based on restriction sites and other features of detection and primer efficiency and were then analysed for interactions. The result in tables 7 and 8 represent no signature detection. A signature detection is represented with the number 1.
  • LSD1 inhibition removes a long range interaction with 5′ upstream to the ORF of MYD88, changing the regulatory landscape for the locus.
  • MYC is the target gene that drives the AML (acute myeloid leukemia) pathology, but at 72 hrs treatment, the fold change is too small to be significant for a marker.
  • the changes seen in Table 9 at the MYC locus at 72 hrs for GEX data correlates to the conformation changes identified at 72 hrs.
  • the negative GEX change at MYC relative to the untreated cells is in keeping with the requirement to perturb MYC proliferation effect. The change is small also in keeping with the tight control elicited on this locus by numerous signal cascades.
  • the EpiSwitchTM biomarkers clearly detect changes in chromosome conformation signatures at 72 hr treatments correspondent with cells differentiation and their death by apoptosis (phenotypic change).
  • the changes seen at MyD88 at 72 hrs for the GEX data correlate to the conformation changes identified at 72 hrs.
  • the GEX change is positive relative to untreated cells, which is in keeping with the differential seen in these AML (acute myeloid leukemia) cells after treatment with the LSD1 inhibitor.
  • Example 3 A Method of Determining the Chromosome Interactions which are Relevant to a Companion Diagnostic for Prognosis of Melanoma Relapse in Treated Patients (PCR Data)
  • a prognostic biomarker predicts the course or outcome (e.g. end, stabilisation or progression) of disease.
  • This study discovers and validates chromosome signatures that could act as prognostic biomarkers for relapse to identify clear epigenetic chromosome conformation differences in monitored melanoma patients, who undergone surgery treatment, for signs of relapse or recovery, and to validate such biomarkers for potential to be prognostic biomarkers for monitoring relapse of melanoma.
  • chromosome conformation signatures in application to confirmed melanoma patients who have undergone treatment by the resection of the original growth in order to identify the candidates who are likely to relapse within 2 years of treatment.
  • Chromosome signatures of 44 genes associated with melanoma and the rest of the genome for any disease-specific long range interaction by Next Generation Sequencing NGS were tested.
  • Non-biased assessment of chromosome signatures associated with melanoma through deep sequencing provided initial pool of 2500 candidate markers.
  • EpiSwitch TM Markers screened and patients used.
  • EpiSwitch TM Melanoma NMSC Markers Screened Patients Used Patients Used 150 4 4 94 14 14 55 21 20 32 74 33 Prognosis of Relapse
  • Top 15 markers previously identified for stratification of melanoma from non-melanoma skin cancers comprise TBx2 7/15, TYR 1/9, TYR 13/17, TYR 3/11, TYR 3/23, P1611/19, P16 7/23, P16 9/29, MITF 35/51, MITF 43/61, MITF 49/55, BRAF 5/11, BRAF 27/31, BRAF 21/31, BRAF 13/21, which were taken from a total of 8 genes: TBx2; TYR; BRAF; MiTF; p 16; BRN2; p 21; TBx3
  • 3C analysis of melanoma patients' epigenetic profiles revealed 150 chromosome signatures with a potential to be prognostic biomarkers, reduced to three in expanding sets of testing sample cohorts.
  • the three chromosome signatures which show the switches in chromosome conformational signature highly consistent with treatment and 2 year outcome for relapse, and this are the best potential prognostic melanoma markers are: BRAF 5/11, p 16-11/19 and TYR 13/17.
  • three chromosome signatures were carried out to the validation stage as prognostic biomarkers.
  • Table 14 shows that relapse has been observed within two years after the treatment among the above patients. Through completely non-biased analysis of chromosome signatures these disease-specific three markers remained present and unchanged after treatment in majority of patients who relapsed after treatment.
  • Table 15 provides evidence that chromosome signatures change as a result of treatment to reflect more healthy profile. Through completely non-biased analysis of chromosome signatures the same disease-specific three markers have changed and were absent in majority of patients after treatment, with no signs of relapse for 2 years.
  • Table 16 shows that the same three prognostic biomarkers show a strong tendency to be absent in healthy population. From all melanoma specific biomarkers identified in initial discovery stage, only these three markers carried prognostic value due to their change after treatment, in that they were different from diagnostic markers.
  • Malignant melanoma is the least common, but most aggressive form of skin cancer. It occurs in melanocytes, cells responsible for synthesis of the dark pigment melanin. The majority of malignant melanomas are caused by heavy UV exposure from the sun. Most of the new melanoma cases are believed to be linked to behavioural changes towards UV exposure from sunlight and sunbeds. Globally, in 2012, melanoma occurred in 232,000 people and resulted in 55,000 deaths. Incidence rates are highest in Australia and New Zealand. The worldwide incidence has been increasing more rapidly amongst men than any other cancer type and has the second fastest incidence increase amongst women over the last decade. The survival rates are very good for individuals with stage 1 and 2 melanomas.
  • the major issue with all immunomodulators currently tested in the treatment of cancers is their low response rates.
  • the objective response rate is only 30-40%.
  • Such therapy is in strong need of biomarkers predicting responders vs. non-responders.
  • the PD-1 locus is regulated by cytokines epigenetically through resetting of long range chromosome conformation signatures.
  • EpiSwitchTM platform technology is ideally suited for stratification of PD-1 epigenetic states prior to and in response to immunotherapy.
  • An EpiSwitchTM array has been designed for analysis of >332 loci implicated in controls and modulation of response to anti-PD-1 treatment in melanoma patients.
  • the hypergeometric analysis was carried out in order to identify regulatory hubs i.e. most densely regulated genes as being potential causative targets and preferred loci for stratification.
  • the data is ranked by the Epigenetic Ratio for R vs R 12W (12W_FC_1), 1 in BL Binary indicates the loop is present in Responders vs Non-Responders, but when Responders baseline are compared to Responders at 12 weeks.
  • the epigenetic ratio indicates that the presence of the loop is more abundant in the 12 week Responder patient samples. This indicates that there has been an expansion of this signature.
  • This epigenetic screen of anti-PD1 therapy for potential predictive and pharmacodynamic biomarkers provides a wealth of new regulatory knowledge, consistent with prior biological evidence.
  • the work provides a rich pool of predictive and pharmacodynamic/response EpiSwitchTM markers to use in validation analysis.
  • the results show presence of a defined epigenetic profile permissive for anti-PD-1 therapy.
  • the epigenetic profile permissive for anti-PD1 therapy is present in na ⁇ ve patients at baseline and is strengthened with treatment over 12 weeks period.
  • EpiSwitchTM as the basis for a diagnostic test to address the issue of poor melanoma diagnosis by general practitioners.
  • 15 lead EpiSwitchTM biomarkers were screened and identified from an initial set of 86 patient samples representing true clinical setting. The biomarkers were then trained and validated in 2 independent patient cohorts: one from Australia (395 patients) and one from the Mayo Clinic (119 patients):
  • the STAT5B_17_40403935_40406459_40464294_40468456_FR probe was measured in Responder v Non-Responder at Baseline and the conformation is present in the Responder. In this comparison the marker is in Responders at 12 weeks, this is the case as the concentrating of DNA used to detect the conformation in Responder vs Non Responder is greater than in Responder baseline v Responder at 12 weeks, indicating the Epigenetic Load has increased in the anti-PD-1 responding patients. Markers STAT5B and IL15 are of particular interest and are involved in key personalised medical and regulatory events responsible for the efficacies response to anti-PD1 therapies (see tables 39 to 40, 43 to 47).
  • Anti-PD1 pharmacodynamic response markers
  • Anti-PD1 pharmacodynamic response markers
  • Anti-PD1 pharmacodynamic response markers—No difference in baseline Responders and baseline Non-Responders but show a significant change in 12 week Responder
  • Probe location Anti-PD1: pharmacodynamic response markers—No difference in baseline Responders and baseline Non-Responders but shows a significant change in 12 week Responders
  • ALS Amyotrophic lateral sclerosis
  • Lou Gehrig's disease is a fatal neurodegenerative disease characterised by progressive death of the primary motor neurones in the central nervous system. Symptoms include muscle weakness and muscle wasting, difficulty in swallowing and undertaking everyday tasks. As the disease progresses, the muscles responsible for breathing gradually fail, causing difficulty in breathing, and finally death.
  • ALS has an average prevalence of 2 per 100,000, but is higher in the UK and USA with up to 5 per 100,000. There are estimated to be over 50,000 patients in the USA and 5,000 patients in the UK with the condition.
  • the mortality rate for ALS sufferers is high: the median survival from diagnosis with ALS (i.e.
  • Primers were designed using Integrated DNA Technologies (IDT) software (and Primer3web version 4.0.0 software if required) from markers identified from the microarray. Primer testing was carried out on each primer set; each set was tested on a pooled subset of samples to ensure that appropriate primers could study the potential interactions. Presence of an amplified product from PCR was taken to indicate the presence of a ligated product, indicating that a particular chromosome interaction was taking place. If the primer testing was successful then the primer sets were taken through to screening.
  • IDT Integrated DNA Technologies
  • the signature set was isolated using a combination of univariate (LIMMA package, R language) and multivariate (GLMNET package, R language) statistics and validated using logistic modelling within WEKA (Machine learning algorithms package).
  • the best 10 stratifying PCR markers were selected for validation on 58 individuals (29 ⁇ ALS; 29 ⁇ Healthy controls—HC) using data from the Northeast Amyotrophic Lateral Sclerosis Consortium (NEALS). These were selected based on their Exact Fisher's P-value. A consistently good marker from all 3 tests was the EpiSwitch marker in CD36.
  • the first 9 PCR markers shown in Table 41 stratified between ALS and HC with 90% rank discrimination index.
  • the ALS marker set was analysed against a small independent cohort of samples provided by Oxford University. Even in a small subset of samples stratification of the samples was shown based on the biomarkers. Four markers stratify the subset of 32 (16 ALS, 16 Healthy Control) samples with p-value ⁇ 0.3. These core markers are ALS.21.23_2, DNM3.5.7_8, ALS.61.63_4 and NEALS.101.103_32, in genes EGFR, DNM3, CD36 and GLYCAM1 respectively. The Fisher-Exact test, GLMNET and Bayesian Logistic modelling marked CLIC4 as a valuable addition to the four core markers.
  • Type 2 diabetes also known as T2DM
  • T2DM Type 2 diabetes
  • Diabetes may occur through either, the pancreas not producing enough hormone insulin which regulates blood sugar levels, or the body not being able to effectively use the hormone it produces due to reduced insulin sensitivity.
  • T2DM has only been diagnosed in adults, but it is now occurring in children and young adults.
  • WHO World Health Organization
  • diabetes reached pandemic levels with 346 million sufferers worldwide and its incidence is predicted to double by 2030.
  • WHO World Health Organization
  • the incidence of T2DM is increasing due to an ageing population, changes in lifestyle such as lack of exercise and smoking, as well as diet and obesity.
  • T2DM is not insulin dependent and can be controlled by changes in lifestyle such as diet, exercise and further aided with medication. Individuals treated with insulin are at a higher risk of developing severe hypoglycaemia (low blood glucose levels) and thus their medication and blood glucose levels require routine monitoring. Generally, older individuals with established T2DM are at a higher risk of cardiovascular disease (CVD) and other complications and thus usually require more treatment than younger adults with a recently-recognised disease. It has been estimated that seven million people in the UK are affected by pre-diabetic conditions, which increase the risk of progressing to T2DM. Such individuals are characterised by raised blood glucose levels, but are usually asymptomatic and thus may be overlooked for many years having a gradual impact on their health.
  • CVD cardiovascular disease
  • Inventors develop prognostic stratifications for pre-diabetic state and T2DM.
  • EpiSwitchTM markers to stratify pre-diabetic state (Pre-T2DM) vs. healthy controls, as well as the discovery of EpiSwitchTM markers to stratify T2DM vs. healthy control, and prognostic markers to stratify aggressive T2DM vs. slow T2DM.
  • Table 29 shows the gene data.
  • Diabetes mellitus (DM) type 1 (also known as T1DM; formerly insulin-dependent diabetes or juvenile diabetes) is a form of diabetes that results from the autoimmune destruction of the insulin-producing beta cells in the pancreas.
  • the classical symptoms are polyuria (frequent urination), polydipsia (increased thirst), polyphagia (increased hunger) and weight loss.
  • T1DM accounts for 5% of all diabetes cases, it is one of the most common endocrine and metabolic conditions among children. Its cause is unknown, but it is believed that both genetic factors and environmental triggers are involved.
  • Globally, the number of people with T1DM is unknown, although it is estimated that about 80,000 children develop the disease each year. The development of new cases varies by country and region.
  • diabetes involves lowering blood glucose and the levels of other known risk factors that damage blood vessels.
  • Administration of insulin is essential for survival. Insulin therapy must be continued indefinitely and does not usually impair normal daily activities. Untreated, diabetes can cause many serious long-term complications such as heart disease, stroke, kidney failure, foot ulcers and damage to the eyes. Acute complications include diabetic ketoacidosis and coma.
  • OBD's diabetes programme is focused on a development of EpiSwitchTM biomarkers for diagnostic and prognostic stratifications of T1DM.
  • EpiSwitchTM markers to stratify T1DM versus healthy controls.
  • T1DM Type 1 diabetes mellitus
  • Ulcerative colitis a chronic inflammatory disease of the gastrointestinal tract, is the most common type of inflammatory disease of the bowel, with an incidence of 10 per 100,000 people annually, and a prevalence of 243 per 100,000.
  • UC Ulcerative colitis
  • Ulcerative colitis can occur in people of any age, it is more likely to develop in people between the ages of 15 and 30 and older than 60.
  • the exact cause of ulcerative colitis is unknown.
  • an overactive intestinal immune system, family history and environmental factors e.g. emotional stress
  • Ulcerative colitis has a well-documented association with the development of colorectal cancer, with greatest risk in longstanding and extensive disease. Treatment of relapse may depend on the clinical severity, extent of disease and patient's preference and may include the use of aminosalicylates, corticosteroids or immunomodulators. The resulting wide choice of agents and dosing regimens has produced widespread heterogeneity in management across the UK, and emphasises the importance of comprehensive guidelines to help healthcare professionals provide consistent high quality care.
  • EpiSwitchTM markers to stratify UC versus healthy controls for a development of disease-specific signatures for UC.
  • SLE Systemic lupus erythematosus
  • discoid lupus or disseminated lupus erythematosus is an autoimmune disease which affects the skin, joints, kidneys, brain, and other organs.
  • SLE is the most common type of lupus. SLE is a disease with a wide array of clinical manifestations including rash, photosensitivity, oral ulcers, arthritis, inflammation of the lining surrounding the lungs and heart, kidney problems, seizures and psychosis, and blood cell abnormalities. Symptoms can vary and can change over time and are not disease specific which makes diagnosis difficult. It occurs from infancy to old age, with peak occurrence between ages 15 and 40.
  • Source Caucasian samples collected by Procurement Company Tissue Solutions based in Glasgow (Samples collected in US); NEALS consortium controls.
  • MS Multiple sclerosis
  • CNS central nervous system
  • MS MS is a potentially highly disabling disorder with considerable personal, social and economic consequences. People with MS live for many years after diagnosis with significant impact on their ability to work, as well as an adverse and often highly debilitating effect on their quality of life and that of their families. OBD's MS programme involves looking at prognostic stratifications between primary progressive and relapsing-remitting MS.
  • MSRR relapsing-remitting MS
  • Most people with this type of MS first experience symptoms in their early 20s. After that, there are periodic attacks (relapses), followed by partial or complete recovery (remissions).
  • the pattern of nerves affected, severity of attacks, degree of recovery, and time between relapses all vary widely from person to person.
  • EpiSwitchTM monitoring markers to stratify MS patients who are responders to IFN-B treatment versus non-responders; EpiSwitchTM markers to stratify MSRR versus healthy controls and EpiSwitchTM markers to stratify MSRR (relapsing remitting type of MS) versus MSPP (primary progressive type of MS).
  • Source Caucasian samples collected by procurement company Tissue Solutions, based in Glasgow (Samples collected in MS-RR: Russia: MS IFN-B R vs NR: USA); NEALS consortium controls (USA
  • MSRR Relapsing-Remitting Multiple Sclerosis
  • MS Multiple Sclerosis
  • NF Neurofibromatosis
  • Table 47 shows the pattern of chromosome interactions present in responders to anti-PD1 (unless otherwise stated with NR (non-responder)) in individuals with particular cancers. The terminology used in the table is explained below.
  • DLBCL_ABC Diffuse large B-cell lymphoma subtype activated B-cells
  • DLBCL_GBC Diffuse large B-cell lymphoma subtype germinal centre B-cells
  • HCC hepatocellular carcinoma
  • HCC_HEPB hepatocellular carcinoma with hepatitis B virus
  • HCC_HEPC hepatocellular carcinoma with hepatitis C virus
  • HEPB+R Hepatitis B in remission
  • Pca_Class3 Prostate cancer stage 3
  • Pca_Class2 Prostate cancer stage 2
  • Pca_Class1 Prostate cancer stage 1
  • PD_1_R_Melanoma Melanoma responder
  • PD_1_NR_Melanoma Melanoma non responder
  • Pre-type 2 diabetes mellitus probes - EpiSwitchTM markers to stratify pre-type 2 diabetes vs. healthy controls Probe Location Probe Chr Start1 End1 Start2 End2 IGF2_11_2162616_2164979_2210793_2214417_RF 11 2162617 2162646 2214388 2214417 ADCY5_3_123037100_123044621_123133741_123143812_RF 3 123037101 123037130 123143783 123143812 TASP1_20_13265932_13269301_13507251_13521471_RR 20 13265933 13265962 13507252 13507281 TNIFRSFB_l_12241967_12245164_12269283_12270518_RR 1 12241968 12241997 12269284 12269313 SREBF1_17_17743896_17753157_17777190_17783023_RF 17 17743897 177439
  • Type 2 diabetes mellitus probes - EpiSwitchTM markers to stratify type 2 diabetes mellitus vs. healthy controls Probe_ Probe_ Count_ Count_ HyperG_ FDR_ Percent_ Probe GeneLocus Total Sig Stats HyperG Sig logFC ICAM1_19_10368390_10370561_10406169_10407761_RF ICAMI 9 5 0.001732 0.070257 55.56 0.454102 SREBF1_17_17743896_17753157_17777190_17783023_RF SREBF1 19 9 0.000113 0.013705 47.37 0.405312 CAMK1D_10_12558950_12568337_12770482_12771684_FR CAMK1D 115 24 0.002791 0.092599 20.87 0.389359 SLC2A2_3_170700264_170710807_170738889_170750047_RF SLC2A2 5 4 0.000
  • Type 2 diabetes mellitus probes - EpiSwitchTM markers to stratify type 2 diabetes mellitus vs. healthy controls Probe AveExpr t P.Value adj.P.Val B ICAM1_19_10368390__10370561_10406169_10407761_RF 0.434102 6.42338 0.000148 0.085141 1.368276 SREBF1_17_17743896_17753157_17777190_17783023_RF 0.405312 4.847825 0.001034 0.085141 ⁇ 0.376824 CAMK1D_10_12558950_12568337_12770482_12771684_FR 0.389359 7.082112 7.22E ⁇ 05 0.085141 1.981818 SLC2A2_3_170700264_170710807_170738889_170750047_RF 0.37933 4.109419 0.0029 0.086908 ⁇ 1.33958 ICAM1_19_1034
  • Type 2 diabetes mellitus probes - Epi SwitchTM markers to stratify type 2 diabetes vs. healthy controls Probe Location Probe Chr Start1 End1 Start2 End2 ICAM1_19_10368390_10370561_10406169_10407761_RF 19 10368391 10368420 10407732 10407761 SREBF1_17_17743896_17753157_17777190_17783023_RF 17 17743897 17743926 17782994 17783023 CAMK1D_10_12558950_12568337_12770482_12771684_FR 10 12568308 12568337 12770483 12770512 SLC2A2_3_170700264_170710807_170738889_170750047_RF 3 170700265 170700294 170750018 170750047 ICAM1_19_10341612_10343024_10406169_10407761_RF 19 10341613 103416
  • Type 1 diabetes meilitus probes - EpiSwitchTM markers to stratify T1DM vs. healthy controls Probe GeneLocus Probe_Count_Total Probe_Count_Sig HyperG_Stats 11_923549_925733_976127_979142_FR AP2A2 16 5 0.059154368 3_3117964_3119702_3187910_3199411_RF IL5RA 7 3 0.060129293 16_4065887_4067896_4109379_4115518_FR ADCY9 66 17 0.007121374 1_172083100_172087823_172151185_172154127_FF DNM3 902 153 0.002933237 16_31228760_31230406_31342509_31344379_FR ITGAM 28 11 0.000764097 1_171936106_171939290_172083100_172087823_RF DNM3 902
  • Type 1 diabetes mellitus probes - EpiSwitch TM markers to stratify T1DM vs. healthy controls Probe AveExpr t P.Value adj.P.Val B 11_923549_925733_976127_979142_FR ⁇ 0.529758172 ⁇ 8.092940735 2.70E ⁇ 06 0.002478464 5.056585897 3_3117964_3119702_3187910_3199411_RF ⁇ 0.472211842 ⁇ 7.326745164 7.60E ⁇ 06 0.002478464 4.088814905 16_4065887_4067896_4109379_4115518_FR ⁇ 0.443525263 ⁇ 4.897708137 0.000334556 0.018676874 0.441359698 1_172083100_172087823_172151185_172154127_FF ⁇ 0.436858249 ⁇ 8.008643893 3.02E ⁇ 06 0.002478464
  • Type 1 diabetes mellitus probes - EpiSwitch TM markers to stratify T1DM vs. healthy controls Probe Probes sequence 60 mer 11_923549_925733_976127_979142_FR GCCTGCAGGGGGCGCCCCCGCGCCTGCCTCGACCACACATCCACATGGACGCATGGCA GG (SEQ ID NO: 257) 3_3117964_3119702_3187910_3199411_RF TGTACAATGTGCTACACCACTCACACCCTCGACAACTTCAGGTAGGAGTGAGTGATAG CT (SEQ ID NO: 258) 16_4065887_4067896_4109379_4115518_FR CGCCGGGCCGACACCCAGATTGTCTTCTTCGAAAAAAAAAAAAAAAAAAAAAAAAAAAAAGAAAAAAAAAGA AA (SEQ ID NO: 259) 1_172083100_172087823_172151185_172154127_FF TCACCTCTGTCACCCACCCGTTCCACT
  • Type 1 diabetes mellitus probes - EpiSwitch TM markers to stratify T1DM vs. healthy controls Probe Location Probe Chr Start1 End1 Start2 End2 11_923549_925733_976127_979142_FR 11 925704 925733 976128 976157 3_3117964_3119702_3187910_3199411_RF 3 3117965 3117994 3199382 3199411 16_4065887_4067896_4109379_4115518_FR 16 4067867 4067896 4109380 4109409 1_172083100_172087823_172151185_172154127_FF 1 172087794 172087823 172154098 172154127 16_31228760_31230406_31342509_31344379_FR 16 31230377 31230406 31342510 31342539 1_171936106_171939290_172083100_17
  • MSRR Relapsing-Remitting Multiple Sclerosis
  • MSRR Multiple Sclerosis
  • Probe sequence 60 1_171811918_171813464_172083100_172087823_RF TCACCTCTGTCACCCACCCGTTCCACTCTCGAATTAGGAATCAGCATTTCTTCCACTG AG (SEQ ID NO: 407) 1_171887726_171889817_172083100_172087823_RF TCACCTCTGTCACCCACCCGTTCCACTCTCGAAATAGTAAAATTTGATTATCAAAATT TT (SEQ ID NO: 408) 11_36588999_36590845_36605543_36609927_FR CCTGTAGCTCTGATGTCAGATGGCAATGTCGATCCACACCACACCAGCAGTGGGGCAC AA (SEQ ID NO: 409) 11_36583119_36588432_36605543_36609927_RR CCACCTCATA
  • MSRR Relapsing-Remitting Multiple Sclerosis
  • MS Multiple Sclerosis
  • B vs. non-responders
  • A Probes 60 mer Probe sequence A 14_24795078_24798615_24843066_24844509_RR CCCACCTCCCACCAGACAGTGGAAGCAGTCGAGTGCTGTGAGCAAAGAGGCCCTG GGCCA (SEQ ID NO: 457) 14_24795078_24798615_24825321_24828950_RR CCCACCTCCCACCAGACAGTGGAAGCAGTCGAAGCAAAACTGTGGAGATTGGGTC GGTGA (SEQ ID NO: 458) 11_923549_925733_976127_979142_FR GCCTGCAGGGGGCGCCCCCGCGCCTGCCTCGACCACACATCCACATGGACGCATG GCAGG (SEQ ID NO: 459) 16_4065887_4067896_4209511_4211354
  • NF Neurofibromatosis
  • MPNSTs Malignant Peripheral Nerve Sheath Tumours
  • Loop Probe LS detected 60 mer Probe sequence A 10_114686118_114690592_114727613_114729725_FF 1 Benign AAGCTCAATAAATCCCAAGCACACACACTCGACCTTCATCACAACAGTGCTCATAGGTTT plexiform (SEQ ID NO: 507) 10_114686118_114690592_114743749_114745454_FF 1 Benign AAGCTCAATAAATCCCAAGCACACACACTCGAGGACCCTTCCACCCAAAAAAAAAAGCAAGG plexiform (SEQ ID NO: 508) 10_114686118_114690592_114773872_114776404_FF 1 Benign AAGCTCAATAAATCCCAAGCACACACACTCGAAGTCAGCT
  • NF neurofibromatosis
  • MPNST Malignant Peripheral Nerve Sheath Tumours
  • Probe Location Probe Chr Start1 End1 Start2 End2 A 10_114686118_114690592_114727613_114729725_FF 10 114690563 114690592 114729696 114729725 10_114686118_114690592_114743749_114745454_FF 10 114690563 114690592 114745425 114745454 10_114686118_114690592_114773872_114776404_FF 10 114690563 114690592 114776375 114776404 10_114686118_114690592_114794603_114795614_FF 10 114690563 114690592 114795585 114795614 10_1146868
  • Pombe protein transporter activity 0.05531008 KCNQ1 Potassium Voltage-Gated Channel, KQT-Like calmodulin binding and voltage-gated potassium 0.05682953 Subfamily, Member 1 channel activity ATP5A1 ATP Synthase, HMitochondrial F1 Complex, ATPase activity and proton-transporting ATPase activity, 0.06838534 Alpha Subunit 1, Cardiac Muscle rotational mechanism WFS1 Wolfram Syndrome 1 (Wolframin) ATPase binding and transporter activity 0.0718483 CCL2 Chemokine (C-C Motif) Ligand 2 heparin binding and receptor binding 0.0726416 ELOVL6 ELOVL Fatty Acid Elongase 6 transferase activity, transferring acyl groups other 0.0726416 than amino-acyl groups IL6 Interleukin 6 (Interferon, Beta 2) interleukin-6 receptor binding and cytokine activity 0.0726416 UCP2 Uncoupling Protein
  • Non-responders - probe sequences Probes 60 mer TNFRSF25_1_6521664_6526267_6541388_6544308_FF CCGCGCCCGCAGGGCCCGCCCCGCGCCGTCGA GGCTTTCAAGGGATCCAGGGTGGGGTGC (SEQ ID NO: 582) TNFRSF25_1_6521664_6526267_6554648_6558108_FR CCGCGCCCGCAGGGCCCGCCCCGCGCCGTCGA CAATGTTATTCTTTGTTTCTCTTACCAA (SEQ ID NO: 583) TNFRSF25_1_6521664_6526267_6554648_6558108_FF CCGCCCGCAGGGCCCGCCCCCCGCCGTCGA TGTGTTGGAAGTCAGGGCGGCGGTGCCC (SEQ ID NO: 584) BOK_2_242498607_242505838_24
  • Anti-PD1 pharmacodynamic response markers Probes Chr Start1 End1 Start2 End2 BAX_19_49417533_49419970_49471563_49474829_FF 19 49419941 49419970 49474800 49474829 BAX_19_49417533_49419970_49435499_49438567_FF 19 49419941 49419970 49438538 49438567 CASP1_11_104941451_104946789_104994205_105005564_RR 11 104941452 104941481 104994206 104994235 NCK2_2_106375590_106379449_106457772_106460967_RR 2 106375591 106375620 106457773 106457802 JAM2_21_26994168_26998383_27012522_27024636_FR 21 26998354 26998383 27012523 27012552 JAM2_21_26
  • Probe location - Anti-PD1 pharmacodynamic response markers -No difference in baseline Responders and baseline Non-Responders but show a significant change in 12 week Responder Probes Chr Start1 End1 Start2 End2 PRKCQ_10_6474855_6481197_6544129_6548414_RF 10 6474856 6474885 6548385 6548414 CBLB_3_105471108_105479961_105538128_105544723_RF 3 105471109 105471138 105544694 105544723 IGKC_2_89162710_89164067_89175040_89179794_FF 2 89164038 89164067 89179765 89179794 CBLB_3_105442255_105450516_105466912_105471108_RR 3 105442256 105442285 105466913 105466942 PRKCQ_10_6474855_6481197_659
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